Abstract [en]

A set of standard answers facilitates answering emails at customer care centers. Matching the text of user emails to the standard answers may not be productive because they do not necessarily have the same wording. Therefore we examine archived email-answer pairs and establish query-answer term co-occurrences. When a new user email arrives, we replace query words with most co-occurring answer words and obtain a “shadow answer”, which is a new query to retrieve standard answers. As a measure of term co-occurrence strength we test raw term co-occurrences and Pointwise Mutual Information.